Abstract: A method, device, system, and computer medium for providing interactive advertising are provided. For example, a device may request an advertisement from a remote server, receive the advertisement, receive a response from a user who is listening and/or watching the advertisement, and transmit the response to the server for further action. The user may input a response by speaking. A server may receive an advertisement request from the device, select an advertisement based on pre-defined one or more criteria, transmit the selected advertisement to the device for play, receive from the device a response to the selected advertisement, and then perform an action corresponding to the received response.

Abstract: Disclosed are a speech processing method and a speech processing apparatus in a 5G communication environment through speech processing by executing embedded artificial intelligence (AI) algorithms and/or machine learning algorithms. The speech processing method includes determining a temporary pause of reception of a first spoken utterance, outputting a first spoken response utterance as a result of speech recognition processing of a second spoken utterance received after the temporary pause, determining, as an extension of the first spoken utterance, a third spoken utterance that is received after outputting the first spoken response utterance, deleting, using a deep neural network model, a duplicate utterance part from a fourth spoken utterance that is obtained by combining the first and the third spoken utterance, and outputting a second spoken response utterance as a result of speech recognition processing of the fourth spoken utterance from which the duplicate utterance part has been deleted.

Abstract: A user, such as an elderly person, may be assisted by an assistance device in his or her caregiving environment that operates in conjunction with one or more server computers. The assistance device may execute a schedule of assistance actions where each assistance action is associated with a time and is executed at that time to assist the user. An assistance action may present an input request to a user, process a voice input of the user, and analyze the voice input to determine that the voice input corresponds to a negative response event, a positive response event, or a non-response event. Based on the categorization of one or more voice inputs as negative response events, positive response events, or non-response events, it may be determined to notify a caregiver of the user, for example where the user has not responded to a number of assistance actions.

Abstract: The present disclosure discloses a method and apparatus for providing a speech service. A specific embodiment of the method comprises: receiving request information sent by a device, the request information comprising first event information and speech information, the first event information used for indicating a first event occurring on the device when the device sends the request information, wherein the first event information comprises speech input event information used for instructing a user to input the speech information; generating response information comprising an operation instruction for a targeted device on the basis of the first event information and the speech information; and sending the response information to the targeted device for the targeted device to perform an operation indicated by the operation instruction. The embodiment improves the efficiency of providing a speech service.

Abstract: Systems and methods are provided for dynamic grammar augmentation for editing multiple network switch configuration files as a single file. The method includes identifying a first base grammar of a first network switch; identifying a second base grammar of a second network switch; identifying first and second patch grammars for the first and second network switches; generating an augmented grammar based on the first and second patch grammars and the first and second base grammars; identifying a first configuration file for the first network switch; identifying a second configuration file for the second network switch; generating a base merged configuration file, the base merged configuration file representing the first and second configuration files modified according to the augmented grammar.

Abstract: One embodiment provides a method, including: receiving, at an information handling device comprising a digital personal assistant, a command; determining, utilizing at least one sensor operatively coupled to the information handling device, a source of the command comprises a source to be ignored; and ignoring, responsive to determining the source is to be ignored, the command. Other aspects are described and claimed.

Abstract: A system and method for determining a target speaker's community of origin from a sound sample of the target speaker is provided. An indexed database of morpheme data from speakers from various communities of origin is provided. Indexed morphemes from a target speaker are extracted. The extracted indexed morphemes from the target speaker are compared against the morpheme data in the indexed database to determine the target speaker's community of origin.

Abstract: An information processing device stores, in a keyword database, keywords extracted from speech sounds picked up by a speech-sound processing device as keywords matching keyword entries in a dictionary database of the speech-sound processing device. The information processing device receives, from the speech-sound processing device, an instruction to update the dictionary database of the speech-sound processing device, and then determines, by inference, words related to the keywords stored in the keyword database, prepares an update of the dictionary database on the basis of the keywords stored in the keyword database and the related words determined by inference, and transmits the update of the dictionary database to the speech-sound processing device.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a dialog system using user feedback. According to one implementation, a method includes receiving, by a dialog engine and from a computing device, a voice input; determining, by the dialog engine, that the received voice input is classified as feedback to an answer of a question; identifying, by the dialog engine, a predetermined feedback score associated with the feedback; and adjusting a confidence score associated with the question and the answer based on the predetermined feedback score.

Abstract: A method for automatic transmission of status information from a first communications terminal set up for speech communication to a second communications terminal set up for text communication is provided. The speech communication between communications terminals is processed over a speech communications server and the text communication between communications terminals over a text communications server. The speech communications server and the text communications server exchange messages over at least one converter device. The status information will be transmitted from the first communications terminal over the speech communications server, the converter device, and the text communications server to the second communications terminal.

Abstract: Methods, systems, and computer-readable media for voice-based parameter assignment for voice-capturing devices are disclosed. Voice input from a voice-capturing device is received over one or more networks at a service provider environment comprising one or more services. The services implement voice input analysis and device management. Using the voice input analysis, analysis of the voice input is performed to determine that the voice input represents a value for a configuration parameter. The value is descriptive of the device. An association between the voice-capturing device and the value for the configuration parameter is stored using the device management. The value affects one or more actions taken by the service provider environment responsive to further voice input from the voice-capturing device.

Abstract: Methods, systems, and media for voice-based call operations are provided. In some embodiments, a method comprises: receiving, at a first user device, a communication; detecting a voice command, using the first user device, that includes a keyword; and in response to detecting the voice command, causing the communication to be transferred to a second user device that is associated with the keyword.

Abstract: Method and system to control a conversational bot uses a directed acyclic graph to specify a desired conversation flow. A graph node has synthetic conversation transcripts annotated with events, wherein an event in a synthetic conversation transcript has preconfigured event expressions that represent ways in which dialogue at the node can unfold. During an on-going conversation with an actor, the system provides a data model uniquely associated with the conversation and that specifies a linear sequence of observations. The data model includes events representing semantically-related conversation fragments located in annotated historical conversation transcripts. In response to receipt of an input in association with a current graph node, the system determines whether the input extends an event in the synthetic conversation transcript associated with the node. If so, a response that continues a current conversation flow in the graph is provided.

Abstract: A system and method for temporarily disabling keyword detection to avoid detection of machine-generated keywords. A local device may operate two keyword detectors. The first keyword detector operates on input audio data received by a microphone to capture keywords uttered by a user. In these instances, the keyword may be detected by the first detector and the audio data may be transmitted to a remote device for processing. The remote device may generate output audio data to be sent to the local device. The local device may process the output audio data to determine that it also includes the keyword. The device may then disable the first keyword detector while the output audio data is played back by an audio speaker of the local device. Thus the local device may avoid detection of a keyword originating from the output audio. The first keyword detector may be reactivated after a time interval during which the keyword might be detectable in the output audio.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for suppressing hotword triggers when detecting a hotword in recorded media are disclosed. In one aspect, a method includes the actions of receiving, by a computing device, audio corresponding to playback of an item of media content. The actions further include determining, by the computing device, that the audio includes an utterance of a predefined hotword and that the audio includes an audio watermark. The actions further include analyzing, by the computing device, the audio watermark. The actions further include based on analyzing the audio watermark, determining, by the computing device, whether to perform speech recognition on a portion of the audio following the predefined hotword.

Abstract: Embodiments of a method and apparatus for processing a speech are provided. The method can include: acquiring, in response to determining at least one speech interaction device in a target speech interaction device set receiving an input speech, a speech feature of the input speech received by a speech interaction device of the at least one speech interaction device; and selecting, based on the speech feature of the input speech received by the speech interaction device in the at least one speech interaction device, a first speech interaction device from the at least one speech interaction device to process the input speech. Some embodiments realize the selection of a targeted speech interaction device.

Abstract: A neural network system for performing a processing task on regulatory content and a method for training the system are disclosed. The method for training involves configuring a neural network language model capable of generating a language embedding output in response to receiving content. The method further involves fine-tuning the language model using regulatory content training data to generate a regulatory content language embedding output for regulatory content processed by the language model. The method also involves configuring at least one task specific output layer to generate task specific results in response to receiving the regulatory content language embedding output from the language model, and training the neural network system using task specific training data to output the task specific results, at least a portion of the task specific training data having been labeled prior to configuring the task specific neural network.

Abstract: A method, system and computer program product for recognizing terms in a specified corpus. In one embodiment, the method comprises providing a set of known terms t?T, each of the known terms t belonging to a set of types ? (t)={?1, . . . }, wherein each of the terms is comprised of a list of words, t=w1, w2, . . . , wn, and the union of all the words for all the terms is a word set W. The method further comprises using the set of terms T and the set of types to determine a set of pattern-to-type mappings p??; and using the set of pattern-to-type mappings to recognize terms in the specified corpus and, for each of the recognized terms in the specified corpus, to recognize one or more of the types ? for said each recognized term.

Abstract: Systems and methods are provided for conducting a simulated conversation with a language learner include determining a first dialog state of the simulated conversation. First audio data corresponding to simulated speech based on the dialog state is transmitted. Second audio data corresponding to a variable length utterance spoken in response to the simulated speech is received. A fixed dimension vector is generated based on the variable length utterance. A semantic label is predicted for the variable-length utterance based on the fixed dimension vector. A second dialog state of the simulated conversation is determined based on the semantic label, and third audio data corresponding to simulated speech is transmitted based on the second dialog state.

Abstract: An apparatus includes processor(s) to: generate a set of candidate n-grams based on probability distributions from an acoustic model for candidate graphemes of a next word most likely spoken following at least one preceding word spoken within speech audio; provide the set of candidate n-grams to multiple devices; provide, to each node device, an indication of which candidate n-grams are to be searched for within the n-gram corpus by each node device to enable searches for multiple candidate n-grams to be performed, independently and at least partially in parallel, across the node devices; receive, from each node device, an indication of a probability of occurrence of at least one candidate n-gram within the speech audio; based on the received probabilities of occurrence, identify the next word most likely spoken within the speech audio; and add the next word most likely spoken to a transcript of the speech audio.